There is an abundance of data, but a large volume of it is unusable. Data may be noisy,
unstructured, stored in incompatible for direct analysis medium or format, and often …

Modern business intelligence requires data processing not only across a huge variety of
domains but also across different paradigms, such as relational, stream, and graph models …

The support for multi-model data has become a standard for most of the existing DBMSs.
However, the step from a conceptual (eg, ER or UML) schema to a logical multi-model …

Changing a database schema is a fact of life in information systems, as a response to
changes inside the enterprise (eg, new users' requirements, correction of errors in the …

The blooming of different data stores has made polystores a major topic in the cloud and big
data landscape. As the amount of data grows rapidly, it becomes critical to exploit the …

Nowadays, data-intensive applications face the problem of handling heterogeneous data
with sometimes mutually exclusive use cases and soft non-functional goals such as …

Polystore databases allow to store data in different formats and data models and offer
several query languages. While such polystore systems are highly beneficial for various …

The support for multi-model data has become a standard for most of the existing DBMSs.
However, the step from a conceptual (eg, ER or UML) schema to a logical multi-model …

The concept of polystore has been proposed and studied for heterogeneous data storage
and cross-model query processing. Correspondingly, the evaluation of diverse polystores is …

The blooming of different cloud data stores has turned polystore systems to a major topic in
the nowadays cloud landscape. Especially, as the amount of processed data grows rapidly …